Barcelona, Catalonia, Spain
Hi, we're UserZoom - nice to meet you! If you’ve never heard of us before, we help companies get the user experience (UX) insights they need to deliver great digital experiences at scale through our all-in-one software platform (both web and mobile) and professional services teams.
We believe that every company will soon be a digital experience company, and we want to help make those digital experiences better. We do this by providing UX insights to some of the biggest brands in the world so they, in turn, can improve the experience they give their customers.
Check out more info here: www.userzoom.com
As part of the Engineering Team, you will have the opportunity to contribute to building on our SaaS platform. Working alongside our global team (our UZ family can be found in the US, UK, Spain, and Poland) you will be responsible for creating something truly amazing - the UX industry is an exciting place to be right now. As UserZoom grows, so does our focus on your career and personal development. And more importantly, the team here at UserZoom is like a family - we're both supportive and welcoming of new team members, with plenty of social events (if you like to get involved).
This is what you'll be doing . . .
- Identifying and implementing the optimal AI solutions to power our automated engines and user-facing features. Maximize robustness, scalability, and maintainability.
- Implementing deployable ML software, collaborating with the Team to bring solid software to production and build a world-class platform.
- Teaming up with product managers to help identify ways that AI can improve our tools. Documenting technical product requirements, translating between the AI and product world.
- Setting up the foundations for a sustainable & scalable AI/ML dimension within the Engineering Team mindset.
- Being a critical referent for the algorithms & solutions under work, able to defend & discuss proposals with managers and teammates.
- Providing technical context and finding key points to boost the best decisions.
- Benchmarking the accuracy and performance of ML solutions, devise acceptance test criteria and strategies, and implement them
- Communicating and documenting solutions, so they can optimally go through building phases.
- Designing scalable & sustainable solutions to absorb the significant usage growth we are facing.
- Being an active player while building, able to take and/or clarify all the aspects.
- Promoting software development best practices, advocating for clean code and helping others succeed through Engineering review processes.
A few things we require for this position . . .
- Creative and intellectually curious people with at least 5 years hands-on experience in machine learning engineering, or 5 years experience in data engineering and a strong attitude for machine learning.
- Working experience with different model architectures and algorithmic approaches.
- Relevant knowledge about artificial intelligence and deep learning solutions, involving algorithms, optimization, reinforcement learning, artificial neural networks, discrete event simulation and case based reasoning.
- Experience training & deploying ML models into production, encompassing coding standards and testing. Working experience in at least one framework, such as TensorFlow, Keras, PyTorch, etc.
- Rigorous thinking towards building at scale and delivering at quality, and designing ML integration in software in terms of ML pipelines.
- MLOPs awareness, with proven experience in building CI/CD pipelines for machine learning models.
- Excellent communication skills, to pose questions with clarity, explain your reasoning concisely, identify the right data points to express a message, and create brief, insightful reports.
- Very good communication skills in English - you're gonna need to use it on a daily basis.
A few things that would be valuable for this position . . .
- SaaS experience in companies responsible for their own product.
- Experience with AWS Services and AI as a Service (AWS / Cloud)
- Fresh views on data analytics & own ideas on how to leverage Data Science across multiple phases.
- Experience with agile environments & tools, collaborating with remote product teams & stakeholders.
- Career path
- Birthday as an additional holiday
- Spanish/ English lessons
- Referral program
- Flexible retribution
- (Zoom) Team building activities
- Flexible working hours
- Private Health insurance (AXA)
- Training & development program
- International working environment